Spatiotemporal Prediction and Mapping of Heavy Metals at Regional Scale Using Regression Methods and Landsat 7

Soil contamination by heavy metals is of particular concern, due to the direct negative impact on crop yield, food quality and human health. Although the conventional approach to monitor heavy metals relies on field sampling and lab analysis, the proliferation in the use of portable spectrometers ha...

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Autores principales:	Abdul M. Mouazen, Felix Nyarko, Muhammad Qaswar, Gergely Tóth, Anne Gobin, Dimitrios Moshou
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	soil heavy metal Landsat 7 partial least squares regression (PLSR) random forest (RF) support vector machine (SVM) spatiotemporal analysis Science Q
Acceso en línea:	https://doaj.org/article/c68d195a79b14ce2b68d57233433887c
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Spatiotemporal Prediction and Mapping of Heavy Metals at Regional Scale Using Regression Methods and Landsat 7

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